Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-4726
Main Title: Tool life prediction for sustainable manufacturing
Author(s): Wang, J.
Wang, P.
Gao, R. X.
Type: Conference Object
Language: English
Language Code: en
Is Part Of: 10.14279/depositonce-3753
Abstract: Prediction of tool wear is essential to maintaining the quality and integrity of machined parts and minimizing material waste, for sustainable manufacturing. Past research has investigated deterministic models such as the Taylor tool life model and its variations for tool wear prediction. Due to the inherent stochastic nature of tool wear and varying operating conditions, the accuracy of such deterministic methods has shown to be limited. This paper presents a stochastic approach to tool wear prediction, based on the particle filter. The technique integrates physics-based tool wear model with measured data to establish a framework, by iteratively updating the tool wear model with force and vibration data measured during the machining process, following the Bayesian updating scheme. Effectiveness of the developed method is demonstrated through tool wear experiments using a ball nose tungsten carbide cutter in a CNC milling machine.
URI: urn:nbn:de:kobv:83-opus4-72283
http://depositonce.tu-berlin.de/handle/11303/5023
http://dx.doi.org/10.14279/depositonce-4726
Issue Date: 2013
Date Available: 8-Oct-2015
DDC Class: 670 Industrielle Fertigung
Subject(s): Bayesian updating
Particle filter
Sustainable manufacturing
Tool wear prediction
Creative Commons License: https://creativecommons.org/licenses/by/3.0/de/
Proceedings Title: Innovative solutions : proceedings / 11th Global Conference on Sustainable Manufacturing, Berlin, Germany, 23rd - 25th September, 2013
Publisher: Universitätsverlag der TU Berlin
Publisher Place: Berlin
Page Start: 230
Page End: 234
Notes: Part of: Seliger, Günther (Ed.): Innovative solutions : proceedings / 11th Global Conference on Sustainable Manufacturing, Berlin, Germany, 23rd - 25th September, 2013. - Berlin: Universitätsverlag der TU Berlin, 2013. - ISBN 978-3-7983-2609-5 (online). - http://nbn-resolving.de/urn:nbn:de:kobv:83-opus4-40276. - pp. 230–234.
Appears in Collections:Technische Universität Berlin » Fakultäten & Zentralinstitute » Fakultät 5 Verkehrs- und Maschinensysteme » Institut für Werkzeugmaschinen und Fabrikbetrieb » Publications

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